What is R? 


R is a free, open-source language used as a statistical and visualization software. It can handle structured as well as semi-structured data.

Features of R:

1.Is available across all platforms, such as Linux, Mac, and Windows

2.Has the ability to integrate with the procedures written in the C, C++, .Net, Python, or FORTRAN languages

3.Has an effective data handling and storage facility

4.Provides a wide variety of integrated collection of tools for data analytics

R has a worldwide repository system –CRAN. The Comprehensive R Archive Network (CRAN) is a network of sites that acts as the primary web service distributing R sources and binaries, extension packages, and documentation.

Why R for Data Analytics?

1.R is a free software.

2.R is a statistical software where complex stats models like linear regression, logistic regression, hypothesis testing, ANOVA(Analysis Of Variance), GLM(Generalized Linear Model), etc., can be run.

3.R has some great tools to aid data visualization to create graphs, bar charts, multi-panel lattice charts, scatter plots, and new custom-designed graphics.

4.Machine Learning algorithms like SVM, NaivesBayes theorem, XGboost, Decision tree, and Random forest are available in R readily. These algorithms have proven to be better over time and provide good accuracy of results.

5.You can now write R codes in SAS as R codes are widely used, and programmers are getting familiar with these.

6.R can handle semi-structured data and has algorithms built.

7.Programmers can define their customized algorithms in R and develop their own algorithms and packages.